Search Results for "databases" - Page 10
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Showing 2245 open source projects for "databases"
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SPQR
Stateless Postgres Query Router
SPQR is a sharding proxy for PostgreSQL that enables horizontal scalability by distributing queries across multiple PostgreSQL instances. Designed for large-scale, multi-tenant architectures, SPQR routes, rewrites, and manages SQL queries to ensure they are executed efficiently across shards. It provides a PostgreSQL-compatible interface so applications can scale transparently without code changes. -
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floci
Light, fluffy, and always free, the AWS Local Emulator alternative
...The project emphasizes no accounts, no authentication gates, no paid feature tiers, and broad local service coverage. It supports many AWS-style services, including storage, queues, databases, identity, compute, streaming, deployment, and infrastructure-related APIs. Floci is useful for development teams that want faster feedback loops, cheaper local testing, and repeatable integration environments. It also includes compatibility testing, multi-account isolation, persistence modes, SDK integration, and migration guidance for teams coming from other local cloud emulators. -
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Superglue
Builds integrations and tools from natural language
Superglue is an AI-powered integration platform that enables developers to build production-grade tools and workflows using natural language, abstracting away the complexity of connecting APIs, databases, and external systems. It functions as a universal integration layer that allows users to define workflows in plain language, which are then translated into executable pipelines capable of interacting with multiple services. One of its defining features is its ability to handle authentication, schema mapping, and data transformation automatically, reducing the need for manual configuration when connecting systems. ... -
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Glances
An eye on your system
...Depending on the size of the user interface, this information can then dynamically adapt. Glances can work in client/server mode, and is also capable of remote monitoring. All systems statistics can be exported to files or external time/value databases. Glances gets information from your system through various libraries, and is based on an open architecture, so you can add new plugins or export modules. -
Error to trace to log to deploy. One click. No SSH.AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
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ADX MCP Server
A Model Context Protocol (MCP) server that enables AI assistants
The Azure Data Explorer MCP Server is a Model Context Protocol (MCP) server that enables AI assistants to query and analyze Azure Data Explorer databases through standardized interfaces. It allows the execution of Kusto Query Language (KQL) queries and exploration of data within Azure Data Explorer clusters. -
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AgentRun
The easiest, and fastest way to run AI-generated Python code safely
AgentRun is a framework for building autonomous AI agents capable of executing complex tasks with minimal human intervention. It provides a structured environment for defining agent behaviors, managing workflows, and integrating AI models to achieve specific goals. -
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Prisma
Next-generation ORM for Node.js and TypeScript
...Prisma Client is a query builder that composes the way you think and gets auto-generated from the Prisma schema with types tailored to your app. We designed the API to be intuitive for both SQL veterans and people brand new to databases. Auto-completion, linting, formatting and more help Prisma developers in VSCode stay confident without distractions. Prisma Client puts extra emphasis on extensive type safety for more productive development in TypeScript. Prisma is a server-side library that helps your app read and write data to the database in an intuitive and safe way. -
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Supabase Wrappers
Postgres Foreign Data Wrapper development framework in Rust
Supabase Wrappers is a collection of PostgreSQL extensions (written in Rust) that allow Postgres to interact with external systems like APIs, files, and other databases. It uses Foreign Data Wrappers (FDWs) to treat external resources as if they were native SQL tables, enabling seamless integration with external services directly from SQL queries. -
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pgai
A suite of tools to develop RAG, semantic search, and other AI apps
pgai is a suite of PostgreSQL extensions developed by Timescale to empower developers in building AI applications directly within their databases. It integrates tools for vector storage, advanced indexing, and AI model interactions, facilitating the development of applications like semantic search and Retrieval-Augmented Generation (RAG) without leaving the SQL environment. -
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freeCodeCamp
freeCodeCamp.org's open-source codebase and curriculum
freeCodeCamp is a nonprofit educational platform that offers a self-paced curriculum for learning web development, programming, data visualization, APIs, and algorithms. It features interactive coding challenges, real-world projects, and guided progress through topic modules, culminating in certificates for completed tracks. A key aspect is that students contribute to open-source projects for nonprofits or internal tooling as part of their learning, reinforcing both technical and... -
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Drizzle ORM
Headless TypeScript ORM with a head. Runs on Node, Bun and Deno
Drizzle ORM is a lightweight, TypeScript-first Object-Relational Mapping (ORM) tool designed for modern JavaScript runtimes. It supports environments like Node.js, Bun, Deno, and even edge runtimes, providing developers with a flexible and type-safe way to interact with databases. Drizzle ORM emphasizes performance and developer experience. -
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Nelmio Alice
Expressive fixtures generator
...It uses YAML, XML, or PHP files to define fixture templates, making it easy to create realistic and varied data sets. Alice integrates well with Doctrine ORM, allowing developers to quickly populate databases with test data, making it especially useful for automated testing and staging environments. -
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Recap
Recap tracks and transform schemas across your whole application
Recap is a schema language and multi-language toolkit to track and transform schemas across your whole application. Your data passes through web services, databases, message brokers, and object stores. Recap describes these schemas in a single language, regardless of which system your data passes through. Recap schemas can be defined in YAML, TOML, JSON, XML, or any other compatible language. -
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Paperclip
Open-source orchestration for zero-human companies
...The project implements a server based on the Model Context Protocol (MCP), a framework that allows large language models and AI agents to connect to external data sources and tools in a consistent way. By acting as a middleware layer, Paperclip aggregates multiple academic databases and exposes them through a single interface, allowing AI applications to search and retrieve scholarly papers without needing to integrate with each provider individually. The system supports repositories such as arXiv, OpenAlex, and the Open Science Framework, giving AI agents access to a large body of research literature. Instead of requiring separate APIs and authentication flows for each service, Paperclip provides unified search and retrieval capabilities that simplify integration into AI workflows. -
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Metabase
The simplest, fastest way to share business intelligence and analytics
...Metabase creates beautiful graphs and charts, with an easy-to-use dashboard where everyone can create, organize and share exceptionally visualized data. It supports a great number of databases, including Postgres, MySQL, Druid, MongoDB, SQLite and more. Setup literally takes 5 minutes. -
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Kangaroo
Kangaroo is an AI-powered SQL client and admin tool for popular dbs
...It allows users to write, analyze, and optimize SQL queries using natural language assistance, making database operations more accessible and efficient. The tool is intended for developers, analysts, and data professionals who want to simplify complex query generation and debugging processes. It integrates with databases to provide context-aware suggestions, helping users understand schema structures and relationships. Kangaroo also supports conversational querying, enabling users to describe what they want to retrieve and receive corresponding SQL queries. The system aims to bridge the gap between traditional database tools and modern AI-driven workflows. ... -
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trustfall
A query engine for any combination of data sources
trustfall is a flexible and extensible query engine designed to retrieve and analyze data from a wide variety of heterogeneous sources using a unified query language. It allows developers to query APIs, databases, files, and even structured outputs from AI systems as if they were part of a single, cohesive graph-based dataset. The system is inspired by GraphQL-like paradigms, enabling expressive and composable queries that can traverse relationships across different data domains seamlessly. Trustfall operates by parsing, compiling, and executing queries through adapters that connect to specific data sources, making it highly modular and adaptable to new environments. ... -
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Cheshire Cat AI
AI agent microservice
...It allows developers to create advanced AI assistants that can interact through WebSockets, REST APIs, and embedded chat interfaces, making it suitable for both backend services and user-facing applications. The framework includes built-in support for retrieval-augmented generation using vector databases such as Qdrant, enabling agents to incorporate external knowledge and documents into their responses. It is highly extensible through a plugin system that supports custom tools, event hooks, and workflows, giving developers fine-grained control over agent behavior and interactions. Cheshire Cat also supports multi-user environments with granular permissions and identity provider integration, making it suitable for enterprise use cases. -
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Memori
SQL-native memory layer enabling persistent context for AI agents
...It provides a memory layer that automatically captures conversations and interactions between users and AI models, allowing systems to retain knowledge across sessions instead of operating statelessly. It extracts structured information such as facts, preferences, rules, and summaries from interactions and stores them in standard SQL databases for later retrieval. By recalling relevant context during future model calls, Memori helps AI agents produce more consistent and context-aware responses while reducing the need to repeatedly provide background information. Memori is designed to work with multiple LLM providers, data stores, and AI frameworks, allowing it to integrate into existing software architectures without requiring major changes. -
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SmythOS
Cloud-native runtime for agentic AI
...It provides a foundational infrastructure layer that functions similarly to an operating system for agentic AI systems, managing resources such as language models, storage, vector databases, and caching through a unified interface. Developers can use the runtime to create, deploy, and orchestrate intelligent agents across local machines, cloud environments, or hybrid infrastructures without rewriting their application logic. The platform includes a software development kit and command-line interface that allow developers to define agent workflows, manage execution environments, and automate deployment processes. ... -
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ReCall
Learning to Reason with Search for LLMs via Reinforcement Learning
...The project builds on earlier work focused on teaching models how to search for information during reasoning tasks and extends that idea to a broader system where models can call a variety of external tools such as APIs, databases, or computation engines. Instead of relying purely on static knowledge stored inside the model, ReCall allows the language model to dynamically decide when it should retrieve information or invoke external capabilities during the reasoning process. The framework uses reinforcement learning to train models to perform these tool calls effectively while solving multi-step reasoning tasks. -
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CAG
Cache-Augmented Generation: A Simple, Efficient Alternative to RAG
CAG, or Cache-Augmented Generation, is an experimental framework that explores an alternative architecture for integrating external knowledge into large language model responses. Traditional retrieval-augmented generation systems rely on real-time retrieval of documents from databases or vector stores during inference. CAG proposes a different approach by preloading relevant knowledge into the model’s context window and precomputing the model’s key-value cache before queries are processed. This strategy allows the model to generate responses using the cached context directly, eliminating the need for repeated retrieval operations during runtime. ... -
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MongoDB Ruby Driver
The Official MongoDB Ruby Driver
The MongoDB Ruby Driver is the official MongoDB client for Ruby applications, providing an idiomatic API to interact with MongoDB databases. It enables seamless integration with Ruby on Rails and other Ruby-based frameworks for NoSQL data management. -
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Jet Database
Type safe SQL builder with code generation and automatic query result
Jet is a complete solution for efficient and high-performance database access, consisting of a type-safe SQL builder with code generation and automatic query result data mapping. Jet currently supports PostgreSQL, MySQL, CockroachDB, MariaDB, and SQLite. Future releases will add support for additional databases. -
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Firebase Admin Python SDK
Firebase Admin Python SDK
...Create your own simplified admin console to do things like look up user data or change a user's email address for authentication. Access Google Cloud resources like Cloud Storage buckets and Cloud Firestore databases associated with your Firebase projects. Programmatically send Firebase Cloud Messaging messages using a simple, alternative approach to the Firebase Cloud Messaging server protocols. We currently support Python 3.7+. Firebase Admin Python SDK is also tested on PyPy and Google App Engine environments.
